Bharath-Shumway Naive Distance-to-Default
Install and import#
npm install fintech-algorithmsimport { bharathShumwayNaiveDistanceToDefault } from "fintech-algorithms/credit-risk-and-default/probability-of-default/bharath-shumway-naive-distance-to-default";Signature#
bharathShumwayNaiveDistanceToDefault(equity_value, debt_face_value, equity_volatility, prior_year_equity_return, horizon_years)Worked example#
verified This is the worked example published in the article, replayed by the test suite on every run. The output cannot drift.
Input#
120800.350.081Call#
bharathShumwayNaiveDistanceToDefault(equity_value, debt_face_value, equity_volatility, prior_year_equity_return, horizon_years)Returns#
object with 7 fields: naive_firm_value, naive_debt_volatility, naive_asset_volatility, naive_distance_to_default, naive_default_probability, state, reason
{
"naive_firm_value": 200,
"naive_debt_volatility": 0.1375,
"naive_asset_volatility": 0.265,
"naive_distance_to_default": 3.62708766745,
"naive_default_probability": 0.000143317997,
"state": "calculated",
"reason": "bharath-shumway-naive-approximation"
}Other exports#
This module also exports
logisticPdModel, probitPdModel, throughTheCyclePd, pointInTimePd, mertonDistanceToDefault, campbellHilscherSzilagyiDistressProbability, calculate. Every module additionally exports run as an alias of its
primary function, and a meta object carrying its catalog id, domain, family,
shape and article URL.
Diagrams#
How it works#
This page states the contract — how to call it correctly. The article explains the concept: why it works, and where it breaks.
References#
- Forecasting Default with the Merton Distance to Default Model — Sreedhar T. Bharath and Tyler Shumway
- On the Pricing of Corporate Debt: The Risk Structure of Interest Rates — Robert C. Merton
- Supervisory Guidance on Model Risk Management — OCC, Board of Governors of the Federal Reserve System, and FDIC
- Evidence boundary